Principal Stratification in Causal Inference
Johns Hopkins University · Harvard University
Abstract
Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by…
Citation impact
- FWCI
- 26.95
- Percentile
- 100%
- References
- 53
Authors
2Topics & keywords
- Causal inference
- Covariate
- Censoring (clinical trials)
- Principal (computer security)
- Principal component analysis
- Econometrics
- Inference
- Statistics
- Peace, Justice and strong institutions